Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Electric vehicle assistant based in driver profile

This paper presents the outcomes of a research work consisting in the development of an Electric Vehicle Assistant (EVA), which creates and stores a driver profile where are contained the driving behaviours related with the EV energy consumption, the EV battery charging information, and the performed routes. This is an application for mobile devices that is able to passively track the driver behaviour and to access several information related with the EV in real time. It is also proposed a range prediction approach based on probability to take into account unpredictable effects of personal driving style, traffic or weather.

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Dissertação de mestrado em Direito dos Contratos e da Empresa

Rheological characterization of EVA and HDPE polymer modified bitumens under large deformation at 20 º C

Large amplitude oscillatory shear (LAOS) coupled with Fourier transform rheology (FTR) was used for the first time to characterize the large deformation behavior of selected bituminous binders at 20 C. Two polymer modified bitumens (PMB) containing recycled EVA and HDPE and two unmodified bitumens were tested with LAOS-FTR. The LAOS-FTR response of all binders was compared at same frequency, at same Deborah number (by tuning the frequency to the relaxation time of each binder) and at same phase shift angle d (by tuning the frequency to the one corresponding to d = 50 in the SAOS response of each sample). In all the approaches, LAOS-FTR results allowed to differentiate between all the nonlinear mechanical characteristics of the tested binders. All binders show LAOS-FTR patterns reminiscent from colloidal dispersions and emulsions. EVA PMB was less prone to strain-induced microstructural changes when compared to HDPE PMB which showed larger values of nonlinear FTR parameters for the range of shear strains tested in LAOS.